code: def _np_array_to_series(
      np_array: np.ndarray, series: pd.Series
  ) -> pd.Series:
      """Convert the `np_array` into a pandas Series.
  
      Parameters
      ----------
      np_array: np.ndarray
          The numpy array that needs to be converted to a pandas Series.
      series: pd.Series
          The pandas Series that contains the name and the index for the `np_array`.
  
      Returns
      -------
      pd.Series
          A view of the numpy array as a pandas Series with index the given series
          its index and name the series its name.
  
      Notes
      -----
      * The constructed series is a pass-by-reference `view` of the numpy array.
      * The given `np_array` receives the same index and name as the `series`.
        Hence, the `np_array` needs to have the same length as the `series`.
      * Giving the `np_array` the **same name as** the `series`, will **result in**
        transforming (i.e., **replacing**) the `series` in the pipeline.
      * When a user does not want a numpy array to replace its input series, it is
        his / her responsibility to create a `pd.Series` (or `pd.DataFrame`) of that
        numpy array with a different (column) name.
  
      """
      # The length of the out has to be the same as the series length
      assert len(np_array) == len(series)
      # Note: pd.Series output holds a view of np_array!
      return pd.Series(
          data=np_array, index=series.index, name=series.name
      )
  
file_path: tsflex/tsflex/processing/series_processor.py
imports: import time
  from typing import Callable, Dict, List, Tuple, Union
  import numpy
  import pandas
  from ..None import __pdoc__
  from ..utils.classes import FrozenClass
  from ..utils.data import flatten, series_dict_to_df, to_list, to_tuple
  from .logger import logger
label_desc: Use image node_id 2 for calling a global function with example usage: _np_array_to_series(np_array, series) and returns: pd